from sentence_transformers import SentenceTransformer

model = SentenceTransformer('D:/ideaSpace/MyPython/models/m3e-base')

#Our sentences we like to encode
sentences = [
    '* Moka 此文本嵌入模型由 MokaAI 训练并开源，训练脚本使用 uniem',
    '* Massive 此文本嵌入模型通过**千万级**的中文句对数据集进行训练',
    '* Mixed 此文本嵌入模型支持中英双语的同质文本相似度计算，异质文本检索等功能，未来还会支持代码检索，ALL in one'
]

#Sentences are encoded by calling model.encode()
embeddings = model.encode(sentences)

#Print the embeddings
for sentence, embedding in zip(sentences, embeddings):
    print("Sentence:", sentence)
    print("Embedding:", embedding)
    print("")
